DeePSC: A Deep Learning Model for Automated Diagnosis of Primary Sclerosing Cholangitis at Two-dimensional MR Cholangiopancreatography.

Purpose: To develop, train, and validate a multiview deep convolutional neural network (DeePSC) for the automated diagnosis of primary sclerosing cholangitis (PSC) on two-dimensional MR cholangiopancreatography (MRCP) images.

Materials And Methods: This retrospective study included two-dimensional MRCP datasets of 342 patients (45 years ± 14 [SD]; 207 male patients) with confirmed diagnosis of PSC and 264 controls (51 years ± 16; 150 male patients). MRCP images were separated into 3-T ( = 361) and 1.

[Sarcoidosis as prime example of a granulomatous disease].

Sarcoidosis is the most frequent immunologically related granulomatous disease and can serve as a model for understanding diseases within this category. The evidence on the diagnostics and treatment is so far limited. It is therefore all the more important that two new and significant guidelines on diagnosis and treatment of sarcoidosis were published during the last 2 years.